The Value of Analytics in Late Stage Recoveries

08 July 2021

I was prompted to write this article after I heard someone say “Data and analytics can’t be valuable at the enforcement stage as it is a statutory process”.

The Just philosophy does not accept this because in a TCF centric environment all creditors need to support an end-to-end operating model that aligns every action to the customer’s circumstances using all the data points available. There are three key pieces to this approach.  

1. Ensuring actions are appropriate: As this is a late-stage process a lot the initial won’t pays have been prompted to pay, and what is left often contains a very diverse population ranging from the obstructive avoiders to the financially vulnerable, and a range between. Our job as a trusted provider of services at this stage of the process is to ensure that we use all of the data available to try to identify potential financial vulnerability and offer support as appropriate as well as identify those that easily have the means to pay and recovery the debt appropriately – Credit Bureau and the associated in house analytics we have developed  is key to this and can give us an indication of someone financial capacity and we can tailor our approach accordingly.

2. Targeting efforts: On a very aged, or previously worked, portfolio it can be uneconomic to work the portfolio for the small returns that are still available from that portfolio. However, through using multiple sources of data propensity score can be attributed to each case and the vast majority of the returns can be made by focusing efforts on the high propensity accounts. As an example, on a recent recycled parking portfolio three sources of data were key to building a reliable propensity score:

  • Bureau data – actually showed that a proportion of cases were still credit active an address were the previous provider returned the cases as gone away.
  • Property data – using a property data provider we are able to tell more about the property, transience index, rented, drive way etc.
  • Vehicle data – Car type, active MOT and Tax are all good indicators of collectability.

3. Segmentation and continual improvement – leveraging specialism within a broad panel: Whilst at the top level two enforcement agencies may look like they have similar performance this can have large variances when looking at the segments, some overall poor performers can actually be the best at some niche segments.  We are fortunate at Just to have a broad set of outcome data from a range of providers with this data we can identify differences in performance on different types of debt and by investigating why these differences occur we can either:

  • Learn and improve, a best practice of one provider can be rolled out over the whole panel driving an uplift in performance for all.
  • Segment and allocate, if a provider is most effective on a particular (niche) segment or segments that cannot be rolled out we are able to pass them those type of accounts on multiple and future portfolios.

By driving this data-led approach and operating model Just and our industry can ensure that both customers are treated appropriately, and resources are focused efficiently and there is also continued improvements in our industry.

In the enforcement sector there are a finite number of agents, and many have chosen to leave the industry during lockdown. On top of this we are now entering a period where debt levels are increasing, and this will in turn make more demands on our industry.  My response to the person was ‘There has never been a more important time for our sector to use data and analytics to cope and excel in the environment that lays ahead.’

Nick Georgiades
Managing Director